Quick Answer
AI can help judge whether an article is missing meaningful information. We do not think asking it to choose a target word count first is the best way to determine article length.
Our preferred approach is:
define the reader's job → cover what that job requires → stop when additional material stops adding meaningful value.
Length becomes a result rather than a target.
This distinction mattered in our own content workflow because AI can produce almost any requested length. That makes word count easy to satisfy and surprisingly weak as an editorial decision rule.
Article Length Is Really a Scope Problem
Consider two questions.
“Should I start a new AI chat when a conversation gets long?”
That may need a relatively concise explanation of context quality, continuity and when old instructions become noise.
Now consider:
“How can I evaluate whether AI-generated construction instructions are actually buildable?”
That question can require dimensions, material reconciliation, structural components, assembly order, fasteners, clearances, safety and visual consistency.
The second article should probably contain more information.
Not because it has a higher word-count target. It has a larger legitimate scope.
AI Can Write Almost Any Requested Length
This is where generative AI changes the editorial problem.
Ask for 500 words and it can usually produce something.
Ask for 2,000 and it can usually keep going.
Ask for 4,000 and it can often keep going again.
Generation capacity therefore tells us almost nothing about what the subject deserves.
Before AI, the effort required to add another thousand words created some natural friction. With AI, expansion is cheap. Editorial discipline becomes more important because the tool rarely runs out of words before the subject runs out of useful things to say.
We Used Length as a Proxy—and It Started Driving the Work
Our original concern was legitimate: we did not want thin pages.
Length and section-depth measurements helped reveal some underdeveloped articles. The trouble began when those measurements stopped being diagnostic signals and started influencing production decisions.
A naturally narrow subject could look deficient simply because it did not resemble a larger article.
That was backwards.
The scope should determine the content. The content should determine the resulting length.
The Question We Ask AI Now
Instead of:
“How many words should this article be?”
we prefer:
“What important reader questions remain unanswered within the scope of this page?”
Then we inspect the suggestions.
If AI identifies a legitimate missing decision, explanation, example or piece of evidence, we add it.
If the suggestions begin moving into distant background, adjacent subjects or questions that deserve separate pages, the article is probably complete.
Completeness Is Not Infinite
There is always something else that could be said.
A page about AI prompt length could expand into tokenization, context windows, transformer architecture, API economics, the history of prompting and model-specific technical behavior.
Those subjects may be interesting.
They do not all belong on that page.
A finished article is not one for which no additional information exists. It is one for which no necessary in-scope information remains missing.
AI Can Help Challenge Completeness
AI is still useful in this decision.
We can ask it to identify:
questions a first-time reader may still have;
claims that need explanation;
steps that assume knowledge the reader may not possess;
important objections;
or decisions the article raises without resolving.
That is a much stronger use of AI than asking it to invent a number and then write until the number is reached.
What Current Google Guidance Actually Says
Google's people-first guidance explicitly says it does not have a preferred word count. Its current spam policies focus instead on whether pages help users and warn against scaled production of unoriginal content that provides little or no value.
That supports the editorial rule we reached from our own experiments: useful completeness matters more than arbitrary length.
Word Count Still Has a Diagnostic Use
We still report word count.
It can expose anomalies.
A complicated practical guide that somehow contains only a few hundred words deserves inspection. A narrow answer that has expanded to several thousand deserves inspection too.
The number can tell us to look.
It should not decide the verdict.
Worthy Trying Verdict
Can AI help judge completeness? Yes
Should AI pick an arbitrary target length first? Usually no
Best decision rule: Necessary in-scope reader value
Human oversight: Medium
Would we still report word count? Yes
The lesson: The right article length is the amount of useful information the subject actually requires—not the amount of text AI is capable of generating.